AI & MACHINE LEARNING PROGRAM • LEVEL 13 — CLUSTERING

Update a Cluster Centroid with Python

Learn update a cluster centroid with python with a short, executable Python example.

IntermediateCentroidMean

PROBLEM UNDERSTANDING

Input and expected output

Sample input

No input required

Sample output

[3.0, 4.0]

COMPLETE PYTHON PROGRAM

Complete Python implementation

points = [[1,2],[3,4],[5,6]]
centroid = [sum(column)/len(points) for column in zip(*points)]
print(centroid)

CURRENT STEP

Select Start to walk through the important lines.

SELECTED LINE

No line selected

EXPECTED OUTPUT FOR THE SAMPLE

[3.0, 4.0]

0%Step 0 of 0

PROGRAM EXPLANATION

Algorithm and explanation

Initialize the sample values used to update a cluster centroid.
Process the data step by step using Centroid and Mean.
Display the result for update a cluster centroid and compare it with the documented sample output.

This example of update a cluster centroid processes the sample values in a controlled iteration. It demonstrates Centroid and Mean and prints a deterministic result that can be checked against the sample output.

EFFICIENCY

Time and space complexity

Time complexity

O(n)

Auxiliary space

O(1)

DEBUGGING CHECKLIST

Common mistakes

Check this

For update a cluster centroid, keep the data shape and value types consistent with Centroid.

Check this

Keep every dependent statement inside the correct indented Python block.

Check this

Check denominators, numeric ranges and rounding before comparing the calculated value.

Try it yourself

Practice: Run the program with the sample input, predict its output, and then test one boundary case of your own.